Guided patch-wise nonlocal SAR despeckling

We propose a new method for SAR image despeckling which leverages information drawn from co-registered optical imagery. Filtering is performed by plain patch-wise nonlocal means, operating exclusively on SAR data. However, the filtering weights are computed by taking into account also the optical guide, which is much cleaner than the SAR data, and hence more discriminative. To avoid injecting optical-domain information into the filtered image, a SAR-domain statistical test is preliminarily performed to reject right away any risky predictor. Experiments on two SAR-optical datasets prove the proposed method to suppress very effectively the speckle, preserving structural details, and without introducing visible filtering artifacts. Overall, the proposed method compares favourably with all state-of-the-art despeckling filters, and also with our own previous optical-guided filter

Modified Fuzzy-Anisotropic Gaussian Kernel and CRB in Denoising SAR Image

Radar speckle noise is often modeled as multiplicative noise for such that higher the intensity higher the speckle noise. As a result, the brighter pixel values are having more noise. The presence of speckle not only complicates visual image interpretation but also the classification of automated image is difficult in corrupted SAR image. Therefore, speckle has to be reduced before analyzing the SAR image.Thus, speckle is the main problem (mingled) in Synthetic Aperture Radar (SAR) images. Speckle is existed due to constructive and destructive interference of coherent signal. In order to reduce it, we approach enhanced kernel based filter. Till there are so many techniques are developed to remove speckle content in SAR system. But no proper technique as been developed to remove speckle content completely. In our project MMSE based filter technique is used. We propose a new integrated Fuzzy Anisotropic Gaussian Kernel (FAGK) for denoising Synthetic Aperture Radar (SAR) Images. Here, texture information lies on principal orientation should be multiplied with fuzzy membership function through the anisotropic Gaussian kernel. It presents Cramer -Rao Bound (CRB) which can be estimated by taking ensemble of texture modeled covariance matrix for different denoising methods. Later, CRB can be found for an index of speckle suppression. Thus, developed filter gives good result in preservation of texture and in structure enhancement. It also presents evaluation of speckle suppression ability, where an index named SMPI (Speckle Suppression and Mean Preservation Index). It compares CRB for the evaluation of SMPI index with different denoising method

Information extraction and transmission techniques for spaceborne synthetic aperture radar images

Information extraction and transmission techniques for synthetic aperture radar (SAR) imagery were investigated. Four interrelated problems were addressed. An optimal tonal SAR image classification algorithm was developed and evaluated. A data compression technique was developed for SAR imagery which is simple and provides a 5:1 compression with acceptable image quality. An optimal textural edge detector was developed. Several SAR image enhancement algorithms have been proposed. The effectiveness of each algorithm was compared quantitatively